Myopia (nearsightedness) is the most common human eye disorder. Familial aggregation studies have strongly supported that genetic factors play an important role in myopia development. Furthermore, epidemiological studies have shown that environmental factors play an important role in myopia development. However, our understanding of the genetic factors and gene-environment interaction associated with myopia is further behind than for other eye disorders such as age-related macular degeneration (AMD). While the single nucleotide polymorphism (SNP) has served as a major genetic marker in human genetic studies, copy number variants (CNVs) have gained much attention lately and can be important to the development of complex human diseases. One major advantage of the whole genome high density SNP chip is that it can generate both SNP and CNV data. However, existing methods of detecting CNVs based on SNP information are relatively new and still in an exploratory stage. To our knowledge, this type of CNV data has not been investigated for myopia. In the present application, we propose to utilize whole genome association (WGA) SNP data from the Singapore Cohort study Of the Risk factors for Myopia (SCORM) study to advance our knowledge of CNV detection methods and perform WGA studies using both SNP and CNV data. The SCORM project followed 1797 school children since 1999 and it is one of the few myopia cohorts that has well-characterized myopia clinical and environmental data. This rich dataset provides a great opportunity to enhance knowledge of the genetics of myopia in several ways. Our specific aims are the following: (1) Evaluate existing CNV detection methods using SCORM 550K SNP array data. The known CNV data in the public database will serve as a guideline to determine the sensitivity and specificity of each method. We will also explore a new method, which takes advantage of inner quarter trimmed mean data to detect CNVs. The best method will be used to determine the CNV data in the SCORM dataset. (2) Perform a whole genome association study using SNPs and CNVs as genetic markers. Both main genetic effects and gene-environmental interactions will be investigated. (3) Develop analytical and visualization tools to enhance data interpretation. We plan to develop tools that can designate genomic location and functional information of CNVs detected from the WGA SNP chips as well as visualization tools that can integrate association results from SNPs and CNVs, and linkage disequilibrium (LD) patterns among SNPs and CNVs. Our project is not only developing tools for WGA study using both SNP and CNV data, but also promises to identify susceptibility gene(s) that have direct impact on myopia or interact with certain environmental factors to lead the development of myopia.